About

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Role Description

This role involves developing perception, planning, and control stacks for autonomous systems. You’ll integrate computer vision (CV), SLAM, and reinforcement learning (RL) methods to deliver reliable, real-time performance on constrained hardware.

• Design and implement perception, planning, and control systems for autonomous robots
• Integrate CV, SLAM, and RL to achieve reliable and efficient real-time performance

Qualifications

• Background in robotics, computer science, or engineering
• Proficient in ROS, with hands-on experience in building robotics pipelines
• Strong coding skills in C++ and Python, with libraries like PyTorch, TensorFlow, OpenCV, and NumPy
• Understanding of robotics fundamentals: perception, motion planning, SLAM, and control theory
• Comfortable deploying real-time systems on constrained hardware using CUDA
• Experience with simulation environments such as Gymnasium for RL training
• Care about bridging research and deployment, ensuring robustness in real-world scenarios

Requirements

• Build and optimize robotics software stacks for perception, planning, and control
• Integrate CV, SLAM, and RL algorithms into real-world robotic systems
• Develop scalable robotics pipelines using ROS, PyTorch, TensorFlow, and OpenCV
• Benchmark and validate performance across simulated and real environments
• Optimize models and algorithms for real-time execution on constrained hardware
• Collaborate with researchers and engineers to bring robotics systems from prototype to production

Benefits

• Classified as an hourly contractor to Mercor
• Paid weekly via Stripe Connect, based on hours logged
• Part-time (20–30 hrs/week) with flexible hours—work from anywhere, on your schedule
• Weekly Bonus of $500–$1000 USD per 5 tasks
• Remote and flexible working style